Pandas Profiling Report

Dataset statistics

Number of variables	91
Number of observations	100
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	71.9 KiB
Average record size in memory	736.0 B

Variable types

Categorical	76
Numeric	15

Warnings

`_STATE` has constant value "1.0"	Constant
`QSTVER` has constant value "10.0"	Constant
`QSTLANG` has constant value "1.0"	Constant
`GENHLTH` is highly correlated with `_RFHLTH`	High correlation
`EXERANY2` is highly correlated with `_TOTINDA`	High correlation
`CVDINFR4` is highly correlated with `_MICHD`	High correlation
`CVDCRHD4` is highly correlated with `_MICHD`	High correlation
`ASTHMA3` is highly correlated with `_LTASTH1` and 2 other fields	High correlation
`HAVARTH3` is highly correlated with `_DRDXAR1`	High correlation
`LASTDEN4` is highly correlated with `_DENVST3`	High correlation
`EDUCA` is highly correlated with `_EDUCAG`	High correlation
`EMPLOY1` is highly correlated with `_HCVU651` and 4 other fields	High correlation
`CHILDREN` is highly correlated with `_CHLDCNT`	High correlation
`INCOME2` is highly correlated with `_INCOMG`	High correlation
`DIFFWALK` is highly correlated with `DIFFALON` and 1 other fields	High correlation
`DIFFALON` is highly correlated with `DIFFWALK`	High correlation
`SMOKE100` is highly correlated with `_SMOKER3`	High correlation
`USENOW3` is highly correlated with `_HISPANC` and 1 other fields	High correlation
`ALCDAY5` is highly correlated with `DRNKANY5` and 2 other fields	High correlation
`SEATBELT` is highly correlated with `HIVRISK5` and 2 other fields	High correlation
`HIVTST6` is highly correlated with `HIVRISK5` and 1 other fields	High correlation
`HIVRISK5` is highly correlated with `SEATBELT` and 2 other fields	High correlation
`_METSTAT` is highly correlated with `_URBSTAT`	High correlation
`_URBSTAT` is highly correlated with `_METSTAT`	High correlation
`_IMPRACE` is highly correlated with `_PRACE1` and 6 other fields	High correlation
`_RFHLTH` is highly correlated with `GENHLTH` and 1 other fields	High correlation
`_HCVU651` is highly correlated with `EMPLOY1` and 4 other fields	High correlation
`_TOTINDA` is highly correlated with `EXERANY2`	High correlation
`_MICHD` is highly correlated with `CVDINFR4` and 1 other fields	High correlation
`_LTASTH1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_CASTHM1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_ASTHMS1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_DRDXAR1` is highly correlated with `HAVARTH3`	High correlation
`_DENVST3` is highly correlated with `LASTDEN4`	High correlation
`_PRACE1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_MRACE1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_HISPANC` is highly correlated with `USENOW3` and 1 other fields	High correlation
`_RACE` is highly correlated with `_IMPRACE` and 6 other fields	High correlation
`_RACEG21` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACEGR3` is highly correlated with `USENOW3` and 8 other fields	High correlation
`_RACE_G1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_AGEG5YR` is highly correlated with `EMPLOY1` and 4 other fields	High correlation
`_AGE65YR` is highly correlated with `EMPLOY1` and 4 other fields	High correlation
`_AGE80` is highly correlated with `EMPLOY1` and 5 other fields	High correlation
`_AGE_G` is highly correlated with `EMPLOY1` and 4 other fields	High correlation
`_BMI5` is highly correlated with `_BMI5CAT` and 1 other fields	High correlation
`_BMI5CAT` is highly correlated with `_BMI5` and 1 other fields	High correlation
`_RFBMI5` is highly correlated with `_BMI5` and 1 other fields	High correlation
`_CHLDCNT` is highly correlated with `CHILDREN` and 1 other fields	High correlation
`_EDUCAG` is highly correlated with `EDUCA`	High correlation
`_INCOMG` is highly correlated with `INCOME2`	High correlation
`_SMOKER3` is highly correlated with `SMOKE100` and 1 other fields	High correlation
`_RFSMOK3` is highly correlated with `_SMOKER3`	High correlation
`DRNKANY5` is highly correlated with `ALCDAY5` and 2 other fields	High correlation
`DROCDY3_` is highly correlated with `ALCDAY5` and 2 other fields	High correlation
`_RFBING5` is highly correlated with `_IMPRACE` and 4 other fields	High correlation
`_DRNKWEK` is highly correlated with `_RFBING5` and 1 other fields	High correlation
`_RFDRHV6` is highly correlated with `_RFBING5` and 1 other fields	High correlation
`_RFSEAT2` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_RFSEAT3` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_DRNKDRV` is highly correlated with `ALCDAY5` and 2 other fields	High correlation
`_AIDTST3` is highly correlated with `HIVTST6` and 1 other fields	High correlation
`GENHLTH` is highly correlated with `_RFHLTH`	High correlation
`PHYSHLTH` is highly correlated with `_PHYS14D`	High correlation
`MENTHLTH` is highly correlated with `_MENT14D`	High correlation
`EXERANY2` is highly correlated with `_TOTINDA`	High correlation
`CVDINFR4` is highly correlated with `_MICHD`	High correlation
`CVDCRHD4` is highly correlated with `_MICHD`	High correlation
`ASTHMA3` is highly correlated with `_LTASTH1` and 2 other fields	High correlation
`HAVARTH3` is highly correlated with `_DRDXAR1`	High correlation
`LASTDEN4` is highly correlated with `_DENVST3`	High correlation
`RMVTETH4` is highly correlated with `_EXTETH3`	High correlation
`EDUCA` is highly correlated with `_EDUCAG`	High correlation
`EMPLOY1` is highly correlated with `_AGEG5YR` and 1 other fields	High correlation
`CHILDREN` is highly correlated with `_CHLDCNT`	High correlation
`INCOME2` is highly correlated with `_INCOMG`	High correlation
`DECIDE` is highly correlated with `DIFFALON`	High correlation
`DIFFWALK` is highly correlated with `DIFFALON` and 1 other fields	High correlation
`DIFFALON` is highly correlated with `DECIDE` and 1 other fields	High correlation
`SMOKE100` is highly correlated with `_SMOKER3`	High correlation
`USENOW3` is highly correlated with `_HISPANC`	High correlation
`ALCDAY5` is highly correlated with `DRNKANY5` and 3 other fields	High correlation
`PNEUVAC4` is highly correlated with `_AGE_G`	High correlation
`SEATBELT` is highly correlated with `_RFSEAT2` and 1 other fields	High correlation
`HIVTST6` is highly correlated with `_AIDTST3`	High correlation
`_METSTAT` is highly correlated with `_URBSTAT`	High correlation
`_URBSTAT` is highly correlated with `_METSTAT`	High correlation
`_IMPRACE` is highly correlated with `_PRACE1` and 5 other fields	High correlation
`_RFHLTH` is highly correlated with `GENHLTH` and 1 other fields	High correlation
`_PHYS14D` is highly correlated with `PHYSHLTH`	High correlation
`_MENT14D` is highly correlated with `MENTHLTH`	High correlation
`_HCVU651` is highly correlated with `_AGEG5YR` and 3 other fields	High correlation
`_TOTINDA` is highly correlated with `EXERANY2`	High correlation
`_MICHD` is highly correlated with `CVDINFR4` and 1 other fields	High correlation
`_LTASTH1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_CASTHM1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_ASTHMS1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_DRDXAR1` is highly correlated with `HAVARTH3`	High correlation
`_EXTETH3` is highly correlated with `RMVTETH4`	High correlation
`_DENVST3` is highly correlated with `LASTDEN4`	High correlation
`_PRACE1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_MRACE1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_HISPANC` is highly correlated with `USENOW3`	High correlation
`_RACE` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACEG21` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACEGR3` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACE_G1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_AGEG5YR` is highly correlated with `EMPLOY1` and 4 other fields	High correlation
`_AGE65YR` is highly correlated with `_HCVU651` and 3 other fields	High correlation
`_AGE80` is highly correlated with `_HCVU651` and 3 other fields	High correlation
`_AGE_G` is highly correlated with `EMPLOY1` and 6 other fields	High correlation
`_BMI5` is highly correlated with `_BMI5CAT` and 1 other fields	High correlation
`_BMI5CAT` is highly correlated with `_BMI5` and 1 other fields	High correlation
`_RFBMI5` is highly correlated with `_BMI5` and 1 other fields	High correlation
`_CHLDCNT` is highly correlated with `CHILDREN` and 1 other fields	High correlation
`_EDUCAG` is highly correlated with `EDUCA`	High correlation
`_INCOMG` is highly correlated with `INCOME2`	High correlation
`_SMOKER3` is highly correlated with `SMOKE100` and 1 other fields	High correlation
`_RFSMOK3` is highly correlated with `_SMOKER3`	High correlation
`DRNKANY5` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`DROCDY3_` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`_RFBING5` is highly correlated with `_RFDRHV6`	High correlation
`_DRNKWEK` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`_RFDRHV6` is highly correlated with `_RFBING5`	High correlation
`_RFSEAT2` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_RFSEAT3` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_DRNKDRV` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`_AIDTST3` is highly correlated with `HIVTST6`	High correlation
`GENHLTH` is highly correlated with `_RFHLTH`	High correlation
`PHYSHLTH` is highly correlated with `_PHYS14D`	High correlation
`MENTHLTH` is highly correlated with `_MENT14D`	High correlation
`EXERANY2` is highly correlated with `_TOTINDA`	High correlation
`CVDINFR4` is highly correlated with `_MICHD`	High correlation
`CVDCRHD4` is highly correlated with `_MICHD`	High correlation
`ASTHMA3` is highly correlated with `_LTASTH1` and 2 other fields	High correlation
`HAVARTH3` is highly correlated with `_DRDXAR1`	High correlation
`LASTDEN4` is highly correlated with `_DENVST3`	High correlation
`RMVTETH4` is highly correlated with `_EXTETH3`	High correlation
`EDUCA` is highly correlated with `_EDUCAG`	High correlation
`CHILDREN` is highly correlated with `_CHLDCNT`	High correlation
`INCOME2` is highly correlated with `_INCOMG`	High correlation
`DECIDE` is highly correlated with `DIFFALON`	High correlation
`DIFFWALK` is highly correlated with `DIFFALON` and 1 other fields	High correlation
`DIFFALON` is highly correlated with `DECIDE` and 1 other fields	High correlation
`SMOKE100` is highly correlated with `_SMOKER3`	High correlation
`USENOW3` is highly correlated with `_HISPANC`	High correlation
`ALCDAY5` is highly correlated with `DRNKANY5` and 3 other fields	High correlation
`SEATBELT` is highly correlated with `_RFSEAT2` and 1 other fields	High correlation
`HIVTST6` is highly correlated with `_AIDTST3`	High correlation
`_METSTAT` is highly correlated with `_URBSTAT`	High correlation
`_URBSTAT` is highly correlated with `_METSTAT`	High correlation
`_IMPRACE` is highly correlated with `_PRACE1` and 5 other fields	High correlation
`_RFHLTH` is highly correlated with `GENHLTH` and 1 other fields	High correlation
`_PHYS14D` is highly correlated with `PHYSHLTH`	High correlation
`_MENT14D` is highly correlated with `MENTHLTH`	High correlation
`_HCVU651` is highly correlated with `_AGEG5YR` and 3 other fields	High correlation
`_TOTINDA` is highly correlated with `EXERANY2`	High correlation
`_MICHD` is highly correlated with `CVDINFR4` and 1 other fields	High correlation
`_LTASTH1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_CASTHM1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_ASTHMS1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_DRDXAR1` is highly correlated with `HAVARTH3`	High correlation
`_EXTETH3` is highly correlated with `RMVTETH4`	High correlation
`_DENVST3` is highly correlated with `LASTDEN4`	High correlation
`_PRACE1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_MRACE1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_HISPANC` is highly correlated with `USENOW3`	High correlation
`_RACE` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACEG21` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACEGR3` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_RACE_G1` is highly correlated with `_IMPRACE` and 5 other fields	High correlation
`_AGEG5YR` is highly correlated with `_HCVU651` and 3 other fields	High correlation
`_AGE65YR` is highly correlated with `_HCVU651` and 3 other fields	High correlation
`_AGE80` is highly correlated with `_HCVU651` and 3 other fields	High correlation
`_AGE_G` is highly correlated with `_HCVU651` and 3 other fields	High correlation
`_BMI5` is highly correlated with `_BMI5CAT` and 1 other fields	High correlation
`_BMI5CAT` is highly correlated with `_BMI5` and 1 other fields	High correlation
`_RFBMI5` is highly correlated with `_BMI5` and 1 other fields	High correlation
`_CHLDCNT` is highly correlated with `CHILDREN`	High correlation
`_EDUCAG` is highly correlated with `EDUCA`	High correlation
`_INCOMG` is highly correlated with `INCOME2`	High correlation
`_SMOKER3` is highly correlated with `SMOKE100` and 1 other fields	High correlation
`_RFSMOK3` is highly correlated with `_SMOKER3`	High correlation
`DRNKANY5` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`DROCDY3_` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`_RFBING5` is highly correlated with `_RFDRHV6`	High correlation
`_DRNKWEK` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`_RFDRHV6` is highly correlated with `_RFBING5`	High correlation
`_RFSEAT2` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_RFSEAT3` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_DRNKDRV` is highly correlated with `ALCDAY5` and 3 other fields	High correlation
`_AIDTST3` is highly correlated with `HIVTST6`	High correlation
`CHECKUP1` is highly correlated with `_AGE_G` and 2 other fields	High correlation
`_DENVST3` is highly correlated with `EDUCA` and 3 other fields	High correlation
`ADDEPEV2` is highly correlated with `_MENT14D` and 1 other fields	High correlation
`PNEUVAC4` is highly correlated with `_HCVU651` and 2 other fields	High correlation
`ALCDAY5` is highly correlated with `_HCVU651` and 6 other fields	High correlation
`_RACEG21` is highly correlated with `_RACE_G1` and 5 other fields	High correlation
`_PHYS14D` is highly correlated with `PHYSHLTH` and 6 other fields	High correlation
`PHYSHLTH` is highly correlated with `_PHYS14D` and 6 other fields	High correlation
`ASTHMA3` is highly correlated with `_ASTHMS1` and 2 other fields	High correlation
`_RACE_G1` is highly correlated with `_RACEG21` and 9 other fields	High correlation
`EDUCA` is highly correlated with `_DENVST3` and 8 other fields	High correlation
`CHCOCNCR` is highly correlated with `_PHYS14D`	High correlation
`PERSDOC2` is highly correlated with `_AGEG5YR`	High correlation
`_CHLDCNT` is highly correlated with `_AGE_G` and 7 other fields	High correlation
`_RFSEAT3` is highly correlated with `SEATBELT` and 1 other fields	High correlation
`_METSTAT` is highly correlated with `_URBSTAT`	High correlation
`_HCVU651` is highly correlated with `PNEUVAC4` and 11 other fields	High correlation
`CVDINFR4` is highly correlated with `_MICHD`	High correlation
`_EDUCAG` is highly correlated with `EDUCA` and 3 other fields	High correlation
`_ASTHMS1` is highly correlated with `ASTHMA3` and 4 other fields	High correlation
`_AGE_G` is highly correlated with `CHECKUP1` and 8 other fields	High correlation
`_RFDRHV6` is highly correlated with `ALCDAY5` and 8 other fields	High correlation
`LASTDEN4` is highly correlated with `_DENVST3` and 2 other fields	High correlation
`FLUSHOT6` is highly correlated with `_CHLDCNT` and 3 other fields	High correlation
`_LTASTH1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_INCOMG` is highly correlated with `_HCVU651` and 2 other fields	High correlation
`DECIDE` is highly correlated with `_ASTHMS1` and 3 other fields	High correlation
`SEATBELT` is highly correlated with `_RFSEAT3` and 2 other fields	High correlation
`_BMI5CAT` is highly correlated with `_RFBMI5` and 1 other fields	High correlation
`RMVTETH4` is highly correlated with `_DENVST3` and 8 other fields	High correlation
`_RFSMOK3` is highly correlated with `_SMOKER3`	High correlation
`DIFFDRES` is highly correlated with `LASTDEN4` and 1 other fields	High correlation
`_DRNKWEK` is highly correlated with `_RFDRHV6` and 4 other fields	High correlation
`MEDCOST` is highly correlated with `_BMI5`	High correlation
`_AGEG5YR` is highly correlated with `CHECKUP1` and 11 other fields	High correlation
`_CASTHM1` is highly correlated with `ASTHMA3` and 2 other fields	High correlation
`_URBSTAT` is highly correlated with `_METSTAT`	High correlation
`_RFBMI5` is highly correlated with `_BMI5CAT` and 1 other fields	High correlation
`_RACE` is highly correlated with `_RACEG21` and 9 other fields	High correlation
`DIABETE3` is highly correlated with `_IMPRACE` and 1 other fields	High correlation
`HAVARTH3` is highly correlated with `_PHYS14D` and 2 other fields	High correlation
`CHILDREN` is highly correlated with `_CHLDCNT` and 7 other fields	High correlation
`_RFSEAT2` is highly correlated with `_RFSEAT3` and 1 other fields	High correlation
`SLEPTIM1` is highly correlated with `PHYSHLTH` and 2 other fields	High correlation
`_RACEGR3` is highly correlated with `_RACEG21` and 9 other fields	High correlation
`_TOTINDA` is highly correlated with `EXERANY2`	High correlation
`DROCDY3_` is highly correlated with `ALCDAY5` and 4 other fields	High correlation
`_DUALUSE` is highly correlated with `EDUCA` and 1 other fields	High correlation
`_MRACE1` is highly correlated with `_RACEG21` and 7 other fields	High correlation
`_AGE80` is highly correlated with `CHECKUP1` and 10 other fields	High correlation
`_AGE65YR` is highly correlated with `_CHLDCNT` and 7 other fields	High correlation
`_DRNKDRV` is highly correlated with `ALCDAY5` and 2 other fields	High correlation
`USENOW3` is highly correlated with `ALCDAY5` and 10 other fields	High correlation
`MARITAL` is highly correlated with `_AGE_G` and 2 other fields	High correlation
`_EXTETH3` is highly correlated with `EDUCA` and 2 other fields	High correlation
`SMOKE100` is highly correlated with `_SMOKER3`	High correlation
`CHCCOPD1` is highly correlated with `PHYSHLTH` and 4 other fields	High correlation
`_SMOKER3` is highly correlated with `_RFSMOK3` and 1 other fields	High correlation
`_IMPRACE` is highly correlated with `_RACEG21` and 11 other fields	High correlation
`_DRDXAR1` is highly correlated with `_PHYS14D` and 2 other fields	High correlation
`HIVRISK5` is highly correlated with `_HCVU651` and 4 other fields	High correlation
`DRNKANY5` is highly correlated with `ALCDAY5` and 2 other fields	High correlation
`_MENT14D` is highly correlated with `ADDEPEV2` and 3 other fields	High correlation
`INCOME2` is highly correlated with `_INCOMG` and 1 other fields	High correlation
`EXERANY2` is highly correlated with `_TOTINDA`	High correlation
`_HISPANC` is highly correlated with `_RACE_G1` and 5 other fields	High correlation
`HLTHPLN1` is highly correlated with `_CHLDCNT` and 5 other fields	High correlation
`DIFFWALK` is highly correlated with `_PHYS14D` and 3 other fields	High correlation
`DIFFALON` is highly correlated with `_PHYS14D` and 5 other fields	High correlation
`_BMI5` is highly correlated with `SEATBELT` and 3 other fields	High correlation
`MENTHLTH` is highly correlated with `ADDEPEV2` and 11 other fields	High correlation
`_RFBING5` is highly correlated with `_RACE_G1` and 7 other fields	High correlation
`RENTHOM1` is highly correlated with `USENOW3`	High correlation
`_MICHD` is highly correlated with `CVDINFR4` and 1 other fields	High correlation
`VETERAN3` is highly correlated with `USENOW3` and 1 other fields	High correlation
`_RFHLTH` is highly correlated with `_PHYS14D` and 4 other fields	High correlation
`CVDCRHD4` is highly correlated with `_MICHD`	High correlation
`BLIND` is highly correlated with `EDUCA` and 2 other fields	High correlation
`_PRACE1` is highly correlated with `_RACEG21` and 7 other fields	High correlation
`HIVTST6` is highly correlated with `HIVRISK5` and 1 other fields	High correlation
`EMPLOY1` is highly correlated with `_DENVST3` and 10 other fields	High correlation
`GENHLTH` is highly correlated with `_RFHLTH`	High correlation
`_AIDTST3` is highly correlated with `HIVRISK5` and 1 other fields	High correlation
`SEX1` is highly correlated with `EDUCA` and 6 other fields	High correlation
`QSTVER` is highly correlated with `CHECKUP1` and 74 other fields	High correlation
`CHECKUP1` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_RACEGR3` is highly correlated with `QSTVER` and 12 other fields	High correlation
`_DENVST3` is highly correlated with `QSTVER` and 2 other fields	High correlation
`ADDEPEV2` is highly correlated with `QSTVER` and 2 other fields	High correlation
`PNEUVAC4` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_TOTINDA` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_RACEG21` is highly correlated with `QSTVER` and 8 other fields	High correlation
`_DUALUSE` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_PHYS14D` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_MRACE1` is highly correlated with `QSTVER` and 8 other fields	High correlation
`_AGE65YR` is highly correlated with `QSTVER` and 4 other fields	High correlation
`_DRNKDRV` is highly correlated with `QSTVER` and 3 other fields	High correlation
`ASTHMA3` is highly correlated with `QSTVER` and 5 other fields	High correlation
`_RACE_G1` is highly correlated with `QSTVER` and 12 other fields	High correlation
`SMOKE100` is highly correlated with `QSTVER` and 3 other fields	High correlation
`CHCOCNCR` is highly correlated with `QSTVER` and 2 other fields	High correlation
`CHCCOPD1` is highly correlated with `QSTVER` and 2 other fields	High correlation
`MARITAL` is highly correlated with `QSTVER` and 2 other fields	High correlation
`USENOW3` is highly correlated with `QSTVER` and 7 other fields	High correlation
`_EXTETH3` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_IMPRACE` is highly correlated with `QSTVER` and 12 other fields	High correlation
`PERSDOC2` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_SMOKER3` is highly correlated with `QSTVER` and 4 other fields	High correlation
`_DRDXAR1` is highly correlated with `QSTVER` and 3 other fields	High correlation
`HIVRISK5` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_CHLDCNT` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_MENT14D` is highly correlated with `QSTVER` and 2 other fields	High correlation
`DRNKANY5` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_RFSEAT3` is highly correlated with `QSTVER` and 4 other fields	High correlation
`_METSTAT` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_HCVU651` is highly correlated with `QSTVER` and 5 other fields	High correlation
`EXERANY2` is highly correlated with `QSTVER` and 3 other fields	High correlation
`CVDINFR4` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_ASTHMS1` is highly correlated with `QSTVER` and 5 other fields	High correlation
`CHCKDNY1` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_AGE_G` is highly correlated with `QSTVER` and 5 other fields	High correlation
`_HISPANC` is highly correlated with `QSTVER` and 9 other fields	High correlation
`HLTHPLN1` is highly correlated with `QSTVER` and 4 other fields	High correlation
`_EDUCAG` is highly correlated with `QSTVER` and 3 other fields	High correlation
`DIFFWALK` is highly correlated with `QSTVER` and 4 other fields	High correlation
`DIFFALON` is highly correlated with `QSTVER` and 4 other fields	High correlation
`_RFDRHV6` is highly correlated with `QSTVER` and 8 other fields	High correlation
`FLUSHOT6` is highly correlated with `QSTVER` and 2 other fields	High correlation
`QSTLANG` is highly correlated with `QSTVER` and 74 other fields	High correlation
`_LTASTH1` is highly correlated with `QSTVER` and 5 other fields	High correlation
`DECIDE` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_RFBING5` is highly correlated with `QSTVER` and 8 other fields	High correlation
`CVDSTRK3` is highly correlated with `QSTVER` and 2 other fields	High correlation
`SEATBELT` is highly correlated with `QSTVER` and 4 other fields	High correlation
`CHCSCNCR` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_BMI5CAT` is highly correlated with `QSTVER` and 3 other fields	High correlation
`RENTHOM1` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_RFSMOK3` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_MICHD` is highly correlated with `QSTVER` and 4 other fields	High correlation
`VETERAN3` is highly correlated with `QSTVER` and 2 other fields	High correlation
`CVDCRHD4` is highly correlated with `QSTVER` and 3 other fields	High correlation
`DIFFDRES` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_RFHLTH` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_AIDTST3` is highly correlated with `QSTVER` and 3 other fields	High correlation
`DEAF` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_STATE` is highly correlated with `QSTVER` and 74 other fields	High correlation
`BLIND` is highly correlated with `QSTVER` and 2 other fields	High correlation
`HIVTST6` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_PRACE1` is highly correlated with `QSTVER` and 9 other fields	High correlation
`MEDCOST` is highly correlated with `QSTVER` and 2 other fields	High correlation
`GENHLTH` is highly correlated with `QSTVER` and 4 other fields	High correlation
`_CASTHM1` is highly correlated with `QSTVER` and 5 other fields	High correlation
`_URBSTAT` is highly correlated with `QSTVER` and 2 other fields	High correlation
`_RFBMI5` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_RACE` is highly correlated with `QSTVER` and 12 other fields	High correlation
`DIABETE3` is highly correlated with `QSTVER` and 3 other fields	High correlation
`HAVARTH3` is highly correlated with `QSTVER` and 3 other fields	High correlation
`CHILDREN` is highly correlated with `QSTVER` and 3 other fields	High correlation
`_RFSEAT2` is highly correlated with `QSTVER` and 4 other fields	High correlation
`SEX1` is highly correlated with `QSTVER` and 3 other fields	High correlation
`FLUSHOT6` is uniformly distributed	Uniform

Reproduction

Analysis started	2021-06-01 14:11:43.531171
Analysis finished	2021-06-01 14:12:48.737935
Duration	1 minute and 5.21 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

_STATE
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	100

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	100	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	100	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	100	33.3%
.	100	33.3%
0	100	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	100	50.0%
0	100	50.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	100	33.3%
.	100	33.3%
0	100	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	100	33.3%
.	100	33.3%
0	100	33.3%

GENHLTH
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

3.0	35
2.0	27
4.0	14
5.0	12
1.0	12

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	3.0
3rd row	5.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
3.0	35	35.0%
2.0	27	27.0%
4.0	14	14.0%
5.0	12	12.0%
1.0	12	12.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	35	35.0%
2.0	27	27.0%
4.0	14	14.0%
1.0	12	12.0%
5.0	12	12.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	35	11.7%
2	27	9.0%
4	14	4.7%
5	12	4.0%
1	12	4.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
3	35	17.5%
2	27	13.5%
4	14	7.0%
5	12	6.0%
1	12	6.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	35	11.7%
2	27	9.0%
4	14	4.7%
5	12	4.0%
1	12	4.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	35	11.7%
2	27	9.0%
4	14	4.7%
5	12	4.0%
1	12	4.0%

PHYSHLTH
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	14
Distinct (%)	14.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	58.01

Minimum	1
Maximum	99
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	18.75
median	88
Q3	88
95-th percentile	88
Maximum	99
Range	98
Interquartile range (IQR)	69.25

Descriptive statistics

Standard deviation	36.97760584
Coefficient of variation (CV)	0.6374350256
Kurtosis	-1.643887949
Mean	58.01
Median Absolute Deviation (MAD)	0
Skewness	-0.4891340719
Sum	5801
Variance	1367.343333
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
88	57	57.0%
30	14	14.0%
2	6	6.0%
5	5	5.0%
3	4	4.0%
10	3	3.0%
20	2	2.0%
14	2	2.0%
7	2	2.0%
99	1	1.0%
Other values (4)	4	4.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	1.0%
2	6	6.0%
3	4	4.0%
5	5	5.0%
7	2	2.0%
10	3	3.0%
12	1	1.0%
14	2	2.0%
15	1	1.0%
20	2	2.0%

Value	Count	Frequency (%)
99	1	1.0%
88	57	57.0%
77	1	1.0%
30	14	14.0%
20	2	2.0%
15	1	1.0%
14	2	2.0%
12	1	1.0%
10	3	3.0%
7	2	2.0%

MENTHLTH
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	69.41

Minimum	1
Maximum	99
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	77
median	88
Q3	88
95-th percentile	88
Maximum	99
Range	98
Interquartile range (IQR)	11

Descriptive statistics

Standard deviation	33.48453435
Coefficient of variation (CV)	0.4824165732
Kurtosis	-0.1663766513
Mean	69.41
Median Absolute Deviation (MAD)	0
Skewness	-1.309242692
Sum	6941
Variance	1121.21404
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
88	73	73.0%
2	6	6.0%
30	5	5.0%
10	4	4.0%
3	3	3.0%
1	3	3.0%
77	2	2.0%
15	2	2.0%
20	1	1.0%
99	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	3	3.0%
2	6	6.0%
3	3	3.0%
10	4	4.0%
15	2	2.0%
20	1	1.0%
30	5	5.0%
77	2	2.0%
88	73	73.0%
99	1	1.0%

Value	Count	Frequency (%)
99	1	1.0%
88	73	73.0%
77	2	2.0%
30	5	5.0%
20	1	1.0%
15	2	2.0%
10	4	4.0%
3	3	3.0%
2	6	6.0%
1	3	3.0%

HLTHPLN1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	92
2.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	92	92.0%
2.0	8	8.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	92	92.0%
2.0	8	8.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	92	30.7%
2	8	2.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	92	46.0%
2	8	4.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	92	30.7%
2	8	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	92	30.7%
2	8	2.7%

PERSDOC2
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	77
2.0	17
3.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	77	77.0%
2.0	17	17.0%
3.0	6	6.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	77	77.0%
2.0	17	17.0%
3.0	6	6.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	77	25.7%
2	17	5.7%
3	6	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	77	38.5%
2	17	8.5%
3	6	3.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	77	25.7%
2	17	5.7%
3	6	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	77	25.7%
2	17	5.7%
3	6	2.0%

MEDCOST
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	94
1.0	5
9.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	94	94.0%
1.0	5	5.0%
9.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	94	94.0%
1.0	5	5.0%
9.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	94	31.3%
1	5	1.7%
9	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	94	47.0%
1	5	2.5%
9	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	94	31.3%
1	5	1.7%
9	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	94	31.3%
1	5	1.7%
9	1	0.3%

CHECKUP1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	88
2.0	5
7.0	3
4.0	3
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	88	88.0%
2.0	5	5.0%
7.0	3	3.0%
4.0	3	3.0%
3.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	88	88.0%
2.0	5	5.0%
4.0	3	3.0%
7.0	3	3.0%
3.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	88	29.3%
2	5	1.7%
4	3	1.0%
7	3	1.0%
3	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	88	44.0%
2	5	2.5%
4	3	1.5%
7	3	1.5%
3	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	88	29.3%
2	5	1.7%
4	3	1.0%
7	3	1.0%
3	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	88	29.3%
2	5	1.7%
4	3	1.0%
7	3	1.0%
3	1	0.3%

EXERANY2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	54
2.0	46

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	54	27.0%
2	46	23.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

SLEPTIM1
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	9
Distinct (%)	9.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.54

Minimum	4
Maximum	77
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	4
5-th percentile	4.95
Q1	6
median	7
Q3	8
95-th percentile	10.1
Maximum	77
Range	73
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	9.971089522
Coefficient of variation (CV)	1.167574886
Kurtosis	44.60969897
Mean	8.54
Median Absolute Deviation (MAD)	1
Skewness	6.660058699
Sum	854
Variance	99.42262626
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
6	26	26.0%
8	23	23.0%
7	22	22.0%
10	7	7.0%
5	7	7.0%
9	5	5.0%
4	5	5.0%
12	3	3.0%
77	2	2.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	5	5.0%
5	7	7.0%
6	26	26.0%
7	22	22.0%
8	23	23.0%
9	5	5.0%
10	7	7.0%
12	3	3.0%
77	2	2.0%

Value	Count	Frequency (%)
77	2	2.0%
12	3	3.0%
10	7	7.0%
9	5	5.0%
8	23	23.0%
7	22	22.0%
6	26	26.0%
5	7	7.0%
4	5	5.0%

CVDINFR4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	92
1.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	92	92.0%
1.0	8	8.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	92	92.0%
1.0	8	8.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	8	2.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	92	46.0%
1	8	4.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	8	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	8	2.7%

CVDCRHD4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	91
1.0	9

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
2.0	91	91.0%
1.0	9	9.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	91	91.0%
1.0	9	9.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	91	30.3%
1	9	3.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	91	45.5%
1	9	4.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	91	30.3%
1	9	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	91	30.3%
1	9	3.0%

CVDSTRK3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	93
1.0	7

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	1.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	93	93.0%
1.0	7	7.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	93	93.0%
1.0	7	7.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	93	31.0%
1	7	2.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	93	46.5%
1	7	3.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	93	31.0%
1	7	2.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	93	31.0%
1	7	2.3%

ASTHMA3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	87
1.0	13

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
2.0	87	87.0%
1.0	13	13.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	87	87.0%
1.0	13	13.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	13	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	87	43.5%
1	13	6.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	13	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	13	4.3%

CHCSCNCR
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	86
1.0	14

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	86	86.0%
1.0	14	14.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	86	86.0%
1.0	14	14.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	86	28.7%
1	14	4.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	86	43.0%
1	14	7.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	86	28.7%
1	14	4.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	86	28.7%
1	14	4.7%

CHCOCNCR
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	84
1.0	16

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	84	84.0%
1.0	16	16.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	84	84.0%
1.0	16	16.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	84	28.0%
1	16	5.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	84	42.0%
1	16	8.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	84	28.0%
1	16	5.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	84	28.0%
1	16	5.3%

CHCCOPD1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	92
1.0	7
7.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	92	92.0%
1.0	7	7.0%
7.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	92	92.0%
1.0	7	7.0%
7.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	7	2.3%
7	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	92	46.0%
1	7	3.5%
7	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	7	2.3%
7	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	7	2.3%
7	1	0.3%

HAVARTH3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	54
2.0	46

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	54	27.0%
2	46	23.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

ADDEPEV2
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	75
1.0	25

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	1.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	75	75.0%
1.0	25	25.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	75	75.0%
1.0	25	25.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	75	25.0%
1	25	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	75	37.5%
1	25	12.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	75	25.0%
1	25	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	75	25.0%
1	25	8.3%

CHCKDNY1
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	91
1.0	9

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	91	91.0%
1.0	9	9.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	91	91.0%
1.0	9	9.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	91	30.3%
1	9	3.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	91	45.5%
1	9	4.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	91	30.3%
1	9	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	91	30.3%
1	9	3.0%

DIABETE3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

3.0	75
1.0	22
4.0	2
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	3.0
2nd row	3.0
3rd row	1.0
4th row	3.0
5th row	4.0

Common Values

Value	Count	Frequency (%)
3.0	75	75.0%
1.0	22	22.0%
4.0	2	2.0%
2.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	75	75.0%
1.0	22	22.0%
4.0	2	2.0%
2.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	75	25.0%
1	22	7.3%
4	2	0.7%
2	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
3	75	37.5%
1	22	11.0%
4	2	1.0%
2	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	75	25.0%
1	22	7.3%
4	2	0.7%
2	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	75	25.0%
1	22	7.3%
4	2	0.7%
2	1	0.3%

LASTDEN4
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.99

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	3
95-th percentile	4
Maximum	9
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.604885219
Coefficient of variation (CV)	0.8064749843
Kurtosis	5.547248546
Mean	1.99
Median Absolute Deviation (MAD)	0
Skewness	2.126069674
Sum	199
Variance	2.575656566
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	62	62.0%
4	15	15.0%
3	12	12.0%
2	8	8.0%
8	2	2.0%
9	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	62	62.0%
2	8	8.0%
3	12	12.0%
4	15	15.0%
8	2	2.0%
9	1	1.0%

Value	Count	Frequency (%)
9	1	1.0%
8	2	2.0%
4	15	15.0%
3	12	12.0%
2	8	8.0%
1	62	62.0%

RMVTETH4
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.33

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	3
Q3	8
95-th percentile	8
Maximum	9
Range	8
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	3.133575104
Coefficient of variation (CV)	0.7236894003
Kurtosis	-1.844359724
Mean	4.33
Median Absolute Deviation (MAD)	2
Skewness	0.2040084266
Sum	433
Variance	9.819292929
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
8	34	34.0%
1	30	30.0%
2	15	15.0%
3	12	12.0%
7	8	8.0%
9	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	30	30.0%
2	15	15.0%
3	12	12.0%
7	8	8.0%
8	34	34.0%
9	1	1.0%

Value	Count	Frequency (%)
9	1	1.0%
8	34	34.0%
7	8	8.0%
3	12	12.0%
2	15	15.0%
1	30	30.0%

SEX1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	64
1.0	35
9.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	64	64.0%
1.0	35	35.0%
9.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	64	64.0%
1.0	35	35.0%
9.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	64	21.3%
1	35	11.7%
9	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	64	32.0%
1	35	17.5%
9	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	64	21.3%
1	35	11.7%
9	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	64	21.3%
1	35	11.7%
9	1	0.3%

MARITAL
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	44
3.0	33
2.0	13
5.0	8
4.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.0
2nd row	5.0
3rd row	3.0
4th row	2.0
5th row	3.0

Common Values

Value	Count	Frequency (%)
1.0	44	44.0%
3.0	33	33.0%
2.0	13	13.0%
5.0	8	8.0%
4.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	44	44.0%
3.0	33	33.0%
2.0	13	13.0%
5.0	8	8.0%
4.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	44	14.7%
3	33	11.0%
2	13	4.3%
5	8	2.7%
4	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	44	22.0%
3	33	16.5%
2	13	6.5%
5	8	4.0%
4	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	44	14.7%
3	33	11.0%
2	13	4.3%
5	8	2.7%
4	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	44	14.7%
3	33	11.0%
2	13	4.3%
5	8	2.7%
4	2	0.7%

EDUCA
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.7

Minimum	2
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	2
5-th percentile	3
Q1	4
median	5
Q3	5
95-th percentile	6
Maximum	9
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.105541597
Coefficient of variation (CV)	0.2352216163
Kurtosis	1.552091818
Mean	4.7
Median Absolute Deviation (MAD)	1
Skewness	0.1189975622
Sum	470
Variance	1.222222222
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
5	36	36.0%
4	29	29.0%
6	22	22.0%
3	9	9.0%
2	3	3.0%
9	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	3	3.0%
3	9	9.0%
4	29	29.0%
5	36	36.0%
6	22	22.0%
9	1	1.0%

Value	Count	Frequency (%)
9	1	1.0%
6	22	22.0%
5	36	36.0%
4	29	29.0%
3	9	9.0%
2	3	3.0%

RENTHOM1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	80
2.0	14
3.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	80	80.0%
2.0	14	14.0%
3.0	6	6.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	80	80.0%
2.0	14	14.0%
3.0	6	6.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	80	26.7%
2	14	4.7%
3	6	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	80	40.0%
2	14	7.0%
3	6	3.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	80	26.7%
2	14	4.7%
3	6	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	80	26.7%
2	14	4.7%
3	6	2.0%

VETERAN3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	87
1.0	12
7.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	87	87.0%
1.0	12	12.0%
7.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	87	87.0%
1.0	12	12.0%
7.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	12	4.0%
7	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	87	43.5%
1	12	6.0%
7	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	12	4.0%
7	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	12	4.0%
7	1	0.3%

EMPLOY1
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	8
Distinct (%)	8.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.08

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	7
Q3	7
95-th percentile	8
Maximum	8
Range	7
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	2.762227179
Coefficient of variation (CV)	0.5437455077
Kurtosis	-1.470012895
Mean	5.08
Median Absolute Deviation (MAD)	1
Skewness	-0.6070863349
Sum	508
Variance	7.62989899
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
7	49	49.0%
1	24	24.0%
8	11	11.0%
2	7	7.0%
5	4	4.0%
3	3	3.0%
6	1	1.0%
4	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	24	24.0%
2	7	7.0%
3	3	3.0%
4	1	1.0%
5	4	4.0%
6	1	1.0%
7	49	49.0%
8	11	11.0%

Value	Count	Frequency (%)
8	11	11.0%
7	49	49.0%
6	1	1.0%
5	4	4.0%
4	1	1.0%
3	3	3.0%
2	7	7.0%
1	24	24.0%

CHILDREN
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

88.0	84
1.0	10
2.0	5
4.0	1

Length

Max length	4
Median length	4
Mean length	3.84
Min length	3

Characters and Unicode

Total characters	384
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	88.0
2nd row	2.0
3rd row	88.0
4th row	88.0
5th row	88.0

Common Values

Value	Count	Frequency (%)
88.0	84	84.0%
1.0	10	10.0%
2.0	5	5.0%
4.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
88.0	84	84.0%
1.0	10	10.0%
2.0	5	5.0%
4.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
8	168	43.8%
.	100	26.0%
0	100	26.0%
1	10	2.6%
2	5	1.3%
4	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	284	74.0%
Other Punctuation	100	26.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
8	168	59.2%
0	100	35.2%
1	10	3.5%
2	5	1.8%
4	1	0.4%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	384	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
8	168	43.8%
.	100	26.0%
0	100	26.0%
1	10	2.6%
2	5	1.3%
4	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	384	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
8	168	43.8%
.	100	26.0%
0	100	26.0%
1	10	2.6%
2	5	1.3%
4	1	0.3%

INCOME2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.97

Minimum	1
Maximum	99
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	7
Q3	8
95-th percentile	99
Maximum	99
Range	98
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	35.14025434
Coefficient of variation (CV)	1.466009776
Kurtosis	0.207201612
Mean	23.97
Median Absolute Deviation (MAD)	2
Skewness	1.439440584
Sum	2397
Variance	1234.837475
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
8	21	21.0%
6	16	16.0%
99	12	12.0%
77	10	10.0%
5	10	10.0%
7	9	9.0%
2	8	8.0%
3	7	7.0%
4	6	6.0%
1	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	1.0%
2	8	8.0%
3	7	7.0%
4	6	6.0%
5	10	10.0%
6	16	16.0%
7	9	9.0%
8	21	21.0%
77	10	10.0%
99	12	12.0%

Value	Count	Frequency (%)
99	12	12.0%
77	10	10.0%
8	21	21.0%
7	9	9.0%
6	16	16.0%
5	10	10.0%
4	6	6.0%
3	7	7.0%
2	8	8.0%
1	1	1.0%

DEAF
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	92
1.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	92	92.0%
1.0	8	8.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	92	92.0%
1.0	8	8.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	8	2.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	92	46.0%
1	8	4.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	8	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	92	30.7%
1	8	2.7%

BLIND
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	95
1.0	5

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	95	95.0%
1.0	5	5.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	95	95.0%
1.0	5	5.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	95	31.7%
1	5	1.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	95	47.5%
1	5	2.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	95	31.7%
1	5	1.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	95	31.7%
1	5	1.7%

DECIDE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	85
1.0	13
7.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	85	85.0%
1.0	13	13.0%
7.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	85	85.0%
1.0	13	13.0%
7.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	85	28.3%
1	13	4.3%
7	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	85	42.5%
1	13	6.5%
7	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	85	28.3%
1	13	4.3%
7	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	85	28.3%
1	13	4.3%
7	2	0.7%

DIFFWALK
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	74
1.0	26

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	74	74.0%
1.0	26	26.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	74	74.0%
1.0	26	26.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	74	24.7%
1	26	8.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	74	37.0%
1	26	13.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	74	24.7%
1	26	8.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	74	24.7%
1	26	8.7%

DIFFDRES
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	96
1.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	96	96.0%
1.0	4	4.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	96	96.0%
1.0	4	4.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	96	32.0%
1	4	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	96	48.0%
1	4	2.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	96	32.0%
1	4	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	96	32.0%
1	4	1.3%

DIFFALON
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	87
1.0	13

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	87	87.0%
1.0	13	13.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	87	87.0%
1.0	13	13.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	13	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	87	43.5%
1	13	6.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	13	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	87	29.0%
1	13	4.3%

SMOKE100
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	58
1.0	42

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	58	58.0%
1.0	42	42.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	58	58.0%
1.0	42	42.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	58	19.3%
1	42	14.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	58	29.0%
1	42	21.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	58	19.3%
1	42	14.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	58	19.3%
1	42	14.0%

USENOW3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

3.0	98
1.0	1
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	2.0%

Sample

1st row	3.0
2nd row	3.0
3rd row	3.0
4th row	3.0
5th row	3.0

Common Values

Value	Count	Frequency (%)
3.0	98	98.0%
1.0	1	1.0%
2.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	98	98.0%
2.0	1	1.0%
1.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	98	32.7%
1	1	0.3%
2	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
3	98	49.0%
1	1	0.5%
2	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	98	32.7%
1	1	0.3%
2	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	98	32.7%
1	1	0.3%
2	1	0.3%

ALCDAY5
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	13
Distinct (%)	13.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	650.18

Minimum	101
Maximum	888
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	101
5-th percentile	106.8
Q1	204.75
median	888
Q3	888
95-th percentile	888
Maximum	888
Range	787
Interquartile range (IQR)	683.25

Descriptive statistics

Standard deviation	333.870034
Coefficient of variation (CV)	0.513504005
Kurtosis	-1.508668831
Mean	650.18
Median Absolute Deviation (MAD)	0
Skewness	-0.703217864
Sum	65018
Variance	111469.1996
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
888	66	66.0%
201	11	11.0%
202	6	6.0%
210	3	3.0%
230	3	3.0%
101	3	3.0%
220	2	2.0%
102	1	1.0%
103	1	1.0%
205	1	1.0%
Other values (3)	3	3.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
101	3	3.0%
102	1	1.0%
103	1	1.0%
107	1	1.0%
201	11	11.0%
202	6	6.0%
203	1	1.0%
204	1	1.0%
205	1	1.0%
210	3	3.0%

Value	Count	Frequency (%)
888	66	66.0%
230	3	3.0%
220	2	2.0%
210	3	3.0%
205	1	1.0%
204	1	1.0%
203	1	1.0%
202	6	6.0%
201	11	11.0%
107	1	1.0%

FLUSHOT6
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	50
2.0	50

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	50	50.0%
2.0	50	50.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	50	50.0%
1.0	50	50.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	50	16.7%
2	50	16.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	50	25.0%
2	50	25.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	50	16.7%
2	50	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	50	16.7%
2	50	16.7%

PNEUVAC4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	53
2.0	43
7.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	53	53.0%
2.0	43	43.0%
7.0	4	4.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	53	53.0%
2.0	43	43.0%
7.0	4	4.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	53	17.7%
2	43	14.3%
7	4	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	53	26.5%
2	43	21.5%
7	4	2.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	53	17.7%
2	43	14.3%
7	4	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	53	17.7%
2	43	14.3%
7	4	1.3%

SEATBELT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	94
3.0	3
5.0	2
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	94	94.0%
3.0	3	3.0%
5.0	2	2.0%
2.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	94	94.0%
3.0	3	3.0%
5.0	2	2.0%
2.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
3	3	1.0%
5	2	0.7%
2	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	94	47.0%
3	3	1.5%
5	2	1.0%
2	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
3	3	1.0%
5	2	0.7%
2	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
3	3	1.0%
5	2	0.7%
2	1	0.3%

HIVTST6
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	81
1.0	17
7.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	81	81.0%
1.0	17	17.0%
7.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	81	81.0%
1.0	17	17.0%
7.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	81	27.0%
1	17	5.7%
7	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	81	40.5%
1	17	8.5%
7	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	81	27.0%
1	17	5.7%
7	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	81	27.0%
1	17	5.7%
7	2	0.7%

HIVRISK5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	98
9.0	1
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	2.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	98	98.0%
9.0	1	1.0%
1.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	98	98.0%
1.0	1	1.0%
9.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	98	32.7%
1	1	0.3%
9	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	98	49.0%
1	1	0.5%
9	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	98	32.7%
1	1	0.3%
9	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	98	32.7%
1	1	0.3%
9	1	0.3%

QSTVER
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

10.0	100

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	400
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	10.0
2nd row	10.0
3rd row	10.0
4th row	10.0
5th row	10.0

Common Values

Value	Count	Frequency (%)
10.0	100	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
10.0	100	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	200	50.0%
1	100	25.0%
.	100	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	300	75.0%
Other Punctuation	100	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	200	66.7%
1	100	33.3%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	400	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	200	50.0%
1	100	25.0%
.	100	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	400	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	200	50.0%
1	100	25.0%
.	100	25.0%

QSTLANG
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	100

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	100	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	100	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	100	33.3%
.	100	33.3%
0	100	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	100	50.0%
0	100	50.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	100	33.3%
.	100	33.3%
0	100	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	100	33.3%
.	100	33.3%
0	100	33.3%

_METSTAT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	70
2.0	30

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	2.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	70	70.0%
2.0	30	30.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	70	70.0%
2.0	30	30.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	70	23.3%
2	30	10.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	70	35.0%
2	30	15.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	70	23.3%
2	30	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	70	23.3%
2	30	10.0%

_URBSTAT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	89
2.0	11

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	89	89.0%
2.0	11	11.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	89	89.0%
2.0	11	11.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	89	29.7%
2	11	3.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	89	44.5%
2	11	5.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	89	29.7%
2	11	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	89	29.7%
2	11	3.7%

_IMPRACE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	81
2.0	13
6.0	5
5.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
6.0	5	5.0%
5.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
6.0	5	5.0%
5.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
6	5	1.7%
5	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	81	40.5%
2	13	6.5%
6	5	2.5%
5	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
6	5	1.7%
5	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
6	5	1.7%
5	1	0.3%

_DUALUSE
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	86
9.0	14

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	9.0
4th row	9.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	86	86.0%
9.0	14	14.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	86	86.0%
9.0	14	14.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	86	28.7%
9	14	4.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	86	43.0%
9	14	7.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	86	28.7%
9	14	4.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	86	28.7%
9	14	4.7%

_RFHLTH
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	74
2.0	26

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	2.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	74	74.0%
2.0	26	26.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	74	74.0%
2.0	26	26.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	74	24.7%
2	26	8.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	74	37.0%
2	26	13.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	74	24.7%
2	26	8.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	74	24.7%
2	26	8.7%

_PHYS14D
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	57
2.0	22
3.0	19
9.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.0
2nd row	1.0
3rd row	2.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	57	57.0%
2.0	22	22.0%
3.0	19	19.0%
9.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	57	57.0%
2.0	22	22.0%
3.0	19	19.0%
9.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	57	19.0%
2	22	7.3%
3	19	6.3%
9	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	57	28.5%
2	22	11.0%
3	19	9.5%
9	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	57	19.0%
2	22	7.3%
3	19	6.3%
9	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	57	19.0%
2	22	7.3%
3	19	6.3%
9	2	0.7%

_MENT14D
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	73
2.0	16
3.0	8
9.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	73	73.0%
2.0	16	16.0%
3.0	8	8.0%
9.0	3	3.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	73	73.0%
2.0	16	16.0%
3.0	8	8.0%
9.0	3	3.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	73	24.3%
2	16	5.3%
3	8	2.7%
9	3	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	73	36.5%
2	16	8.0%
3	8	4.0%
9	3	1.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	73	24.3%
2	16	5.3%
3	8	2.7%
9	3	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	73	24.3%
2	16	5.3%
3	8	2.7%
9	3	1.0%

_HCVU651
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

9.0	60
1.0	32
2.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	9.0
2nd row	2.0
3rd row	9.0
4th row	9.0
5th row	9.0

Common Values

Value	Count	Frequency (%)
9.0	60	60.0%
1.0	32	32.0%
2.0	8	8.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
9.0	60	60.0%
1.0	32	32.0%
2.0	8	8.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
9	60	20.0%
1	32	10.7%
2	8	2.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
9	60	30.0%
1	32	16.0%
2	8	4.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
9	60	20.0%
1	32	10.7%
2	8	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
9	60	20.0%
1	32	10.7%
2	8	2.7%

_TOTINDA
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	54
2.0	46

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	54	27.0%
2	46	23.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

_MICHD
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	86
1.0	14

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
2.0	86	86.0%
1.0	14	14.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	86	86.0%
1.0	14	14.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	86	28.7%
1	14	4.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	86	43.0%
1	14	7.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	86	28.7%
1	14	4.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	86	28.7%
1	14	4.7%

_LTASTH1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	87
2.0	13

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	87	87.0%
2.0	13	13.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	87	87.0%
2.0	13	13.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	87	29.0%
2	13	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	87	43.5%
2	13	6.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	87	29.0%
2	13	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	87	29.0%
2	13	4.3%

_CASTHM1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	90
2.0	10

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	90	90.0%
2.0	10	10.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	90	90.0%
2.0	10	10.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	90	30.0%
2	10	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	90	45.0%
2	10	5.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	90	30.0%
2	10	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	90	30.0%
2	10	3.3%

_ASTHMS1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

3.0	87
1.0	10
2.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.0
2nd row	3.0
3rd row	3.0
4th row	3.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
3.0	87	87.0%
1.0	10	10.0%
2.0	3	3.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	87	87.0%
1.0	10	10.0%
2.0	3	3.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	87	29.0%
1	10	3.3%
2	3	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
3	87	43.5%
1	10	5.0%
2	3	1.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	87	29.0%
1	10	3.3%
2	3	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	87	29.0%
1	10	3.3%
2	3	1.0%

_DRDXAR1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	54
2.0	46

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	54	54.0%
2.0	46	46.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	54	27.0%
2	46	23.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	54	18.0%
2	46	15.3%

_EXTETH3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	57
1.0	34
9.0	9

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	9.0
4th row	2.0
5th row	9.0

Common Values

Value	Count	Frequency (%)
2.0	57	57.0%
1.0	34	34.0%
9.0	9	9.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	57	57.0%
1.0	34	34.0%
9.0	9	9.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	57	19.0%
1	34	11.3%
9	9	3.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	57	28.5%
1	34	17.0%
9	9	4.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	57	19.0%
1	34	11.3%
9	9	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	57	19.0%
1	34	11.3%
9	9	3.0%

_DENVST3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	62
2.0	37
9.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	2.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	62	62.0%
2.0	37	37.0%
9.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	62	62.0%
2.0	37	37.0%
9.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	62	20.7%
2	37	12.3%
9	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	62	31.0%
2	37	18.5%
9	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	62	20.7%
2	37	12.3%
9	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	62	20.7%
2	37	12.3%
9	1	0.3%

_PRACE1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	82
2.0	13
6.0	4
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	82	82.0%
2.0	13	13.0%
6.0	4	4.0%
3.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	82	82.0%
2.0	13	13.0%
6.0	4	4.0%
3.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	82	27.3%
2	13	4.3%
6	4	1.3%
3	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	82	41.0%
2	13	6.5%
6	4	2.0%
3	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	82	27.3%
2	13	4.3%
6	4	1.3%
3	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	82	27.3%
2	13	4.3%
6	4	1.3%
3	1	0.3%

_MRACE1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	82
2.0	13
6.0	3
7.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	82	82.0%
2.0	13	13.0%
6.0	3	3.0%
7.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	82	82.0%
2.0	13	13.0%
6.0	3	3.0%
7.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	82	27.3%
2	13	4.3%
6	3	1.0%
7	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	82	41.0%
2	13	6.5%
6	3	1.5%
7	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	82	27.3%
2	13	4.3%
6	3	1.0%
7	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	82	27.3%
2	13	4.3%
6	3	1.0%
7	2	0.7%

_HISPANC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	99
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	99	99.0%
1.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	99	99.0%
1.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	99	33.0%
1	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	99	49.5%
1	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	99	33.0%
1	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	99	33.0%
1	1	0.3%

_RACE
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	81
2.0	13
6.0	3
7.0	2
8.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
6.0	3	3.0%
7.0	2	2.0%
8.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
6.0	3	3.0%
7.0	2	2.0%
8.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
6	3	1.0%
7	2	0.7%
8	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	81	40.5%
2	13	6.5%
6	3	1.5%
7	2	1.0%
8	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
6	3	1.0%
7	2	0.7%
8	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
6	3	1.0%
7	2	0.7%
8	1	0.3%

_RACEG21
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	81
2.0	19

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	19	19.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	19	19.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	19	6.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	81	40.5%
2	19	9.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	19	6.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	19	6.3%

_RACEGR3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	81
2.0	13
3.0	3
4.0	2
5.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
3.0	3	3.0%
4.0	2	2.0%
5.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
3.0	3	3.0%
4.0	2	2.0%
5.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
3	3	1.0%
4	2	0.7%
5	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	81	40.5%
2	13	6.5%
3	3	1.5%
4	2	1.0%
5	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
3	3	1.0%
4	2	0.7%
5	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
3	3	1.0%
4	2	0.7%
5	1	0.3%

_RACE_G1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	81
2.0	13
4.0	3
5.0	2
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
4.0	3	3.0%
5.0	2	2.0%
3.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	81	81.0%
2.0	13	13.0%
4.0	3	3.0%
5.0	2	2.0%
3.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
4	3	1.0%
5	2	0.7%
3	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	81	40.5%
2	13	6.5%
4	3	1.5%
5	2	1.0%
3	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
4	3	1.0%
5	2	0.7%
3	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	81	27.0%
2	13	4.3%
4	3	1.0%
5	2	0.7%
3	1	0.3%

_AGEG5YR
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.88

Minimum	3
Maximum	13
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	3
5-th percentile	5.9
Q1	8
median	10
Q3	12
95-th percentile	13
Maximum	13
Range	10
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.76442041
Coefficient of variation (CV)	0.2797996366
Kurtosis	-0.4329360869
Mean	9.88
Median Absolute Deviation (MAD)	2
Skewness	-0.6515671241
Sum	988
Variance	7.642020202
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
13	23	23.0%
12	15	15.0%
8	13	13.0%
10	13	13.0%
6	11	11.0%
11	9	9.0%
9	8	8.0%
7	3	3.0%
3	3	3.0%
4	2	2.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3	3	3.0%
4	2	2.0%
6	11	11.0%
7	3	3.0%
8	13	13.0%
9	8	8.0%
10	13	13.0%
11	9	9.0%
12	15	15.0%
13	23	23.0%

Value	Count	Frequency (%)
13	23	23.0%
12	15	15.0%
11	9	9.0%
10	13	13.0%
9	8	8.0%
8	13	13.0%
7	3	3.0%
6	11	11.0%
4	2	2.0%
3	3	3.0%

_AGE65YR
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	60
1.0	40

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	60	60.0%
1.0	40	40.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	60	60.0%
1.0	40	40.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	60	20.0%
1	40	13.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	60	30.0%
1	40	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	60	20.0%
1	40	13.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	60	20.0%
1	40	13.3%

_AGE80
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	32.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	66.26

Minimum	33
Maximum	80
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	33
5-th percentile	45.6
Q1	58
median	68.5
Q3	78
95-th percentile	80
Maximum	80
Range	47
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	12.99853916
Coefficient of variation (CV)	0.1961747533
Kurtosis	-0.2822165511
Mean	66.26
Median Absolute Deviation (MAD)	10.5
Skewness	-0.7530513593
Sum	6626
Variance	168.9620202
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
80	23	23.0%
78	6	6.0%
77	5	5.0%
59	5	5.0%
70	4	4.0%
49	4	4.0%
58	4	4.0%
62	4	4.0%
48	3	3.0%
46	3	3.0%
Other values (22)	39	39.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
33	2	2.0%
34	1	1.0%
37	1	1.0%
38	1	1.0%
46	3	3.0%
47	1	1.0%
48	3	3.0%
49	4	4.0%
50	1	1.0%
54	2	2.0%

Value	Count	Frequency (%)
80	23	23.0%
79	1	1.0%
78	6	6.0%
77	5	5.0%
76	2	2.0%
75	1	1.0%
73	2	2.0%
72	2	2.0%
71	1	1.0%
70	4	4.0%

_AGE_G
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

6.0	60
5.0	21
4.0	14
2.0	3
3.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	6.0
2nd row	2.0
3rd row	6.0
4th row	6.0
5th row	6.0

Common Values

Value	Count	Frequency (%)
6.0	60	60.0%
5.0	21	21.0%
4.0	14	14.0%
2.0	3	3.0%
3.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
6.0	60	60.0%
5.0	21	21.0%
4.0	14	14.0%
2.0	3	3.0%
3.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
6	60	20.0%
5	21	7.0%
4	14	4.7%
2	3	1.0%
3	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
6	60	30.0%
5	21	10.5%
4	14	7.0%
2	3	1.5%
3	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
6	60	20.0%
5	21	7.0%
4	14	4.7%
2	3	1.0%
3	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
6	60	20.0%
5	21	7.0%
4	14	4.7%
2	3	1.0%
3	2	0.7%

_BMI5
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	92
Distinct (%)	92.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2866.01

Minimum	2066
Maximum	4826
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	2066
5-th percentile	2162.8
Q1	2524
median	2732.5
Q3	3125.75
95-th percentile	3808.75
Maximum	4826
Range	2760
Interquartile range (IQR)	601.75

Descriptive statistics

Standard deviation	532.254847
Coefficient of variation (CV)	0.1857128367
Kurtosis	1.879842989
Mean	2866.01
Median Absolute Deviation (MAD)	295
Skewness	1.150019496
Sum	286601
Variance	283295.2221
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2582	3	3.0%
3320	2	2.0%
2663	2	2.0%
2524	2	2.0%
2929	2	2.0%
2744	2	2.0%
3298	2	2.0%
2577	1	1.0%
3128	1	1.0%
3524	1	1.0%
Other values (82)	82	82.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2066	1	1.0%
2120	1	1.0%
2141	1	1.0%
2146	1	1.0%
2159	1	1.0%
2163	1	1.0%
2177	1	1.0%
2179	1	1.0%
2231	1	1.0%
2249	1	1.0%

Value	Count	Frequency (%)
4826	1	1.0%
4629	1	1.0%
4120	1	1.0%
4069	1	1.0%
3975	1	1.0%
3800	1	1.0%
3759	1	1.0%
3730	1	1.0%
3524	1	1.0%
3502	1	1.0%

_BMI5CAT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

3.0	44
4.0	33
2.0	23

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	4.0
3rd row	3.0
4th row	3.0
5th row	4.0

Common Values

Value	Count	Frequency (%)
3.0	44	44.0%
4.0	33	33.0%
2.0	23	23.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	44	44.0%
4.0	33	33.0%
2.0	23	23.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	44	14.7%
4	33	11.0%
2	23	7.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
3	44	22.0%
4	33	16.5%
2	23	11.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	44	14.7%
4	33	11.0%
2	23	7.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	44	14.7%
4	33	11.0%
2	23	7.7%

_RFBMI5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	77
1.0	23

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	77	77.0%
1.0	23	23.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	77	77.0%
1.0	23	23.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	77	25.7%
1	23	7.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	77	38.5%
1	23	11.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	77	25.7%
1	23	7.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	77	25.7%
1	23	7.7%

_CHLDCNT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	84
2.0	10
3.0	5
5.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	3.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	84	84.0%
2.0	10	10.0%
3.0	5	5.0%
5.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	84	84.0%
2.0	10	10.0%
3.0	5	5.0%
5.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	84	28.0%
2	10	3.3%
3	5	1.7%
5	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	84	42.0%
2	10	5.0%
3	5	2.5%
5	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	84	28.0%
2	10	3.3%
3	5	1.7%
5	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	84	28.0%
2	10	3.3%
3	5	1.7%
5	1	0.3%

_EDUCAG
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

3.0	36
2.0	29
4.0	22
1.0	12
9.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	4.0
2nd row	4.0
3rd row	2.0
4th row	2.0
5th row	3.0

Common Values

Value	Count	Frequency (%)
3.0	36	36.0%
2.0	29	29.0%
4.0	22	22.0%
1.0	12	12.0%
9.0	1	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	36	36.0%
2.0	29	29.0%
4.0	22	22.0%
1.0	12	12.0%
9.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	36	12.0%
2	29	9.7%
4	22	7.3%
1	12	4.0%
9	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
3	36	18.0%
2	29	14.5%
4	22	11.0%
1	12	6.0%
9	1	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	36	12.0%
2	29	9.7%
4	22	7.3%
1	12	4.0%
9	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
3	36	12.0%
2	29	9.7%
4	22	7.3%
1	12	4.0%
9	1	0.3%

_INCOMG
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.77

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	3
median	5
Q3	5
95-th percentile	9
Maximum	9
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.589235681
Coefficient of variation (CV)	0.5428167047
Kurtosis	-0.7695804194
Mean	4.77
Median Absolute Deviation (MAD)	2
Skewness	0.5012533516
Sum	477
Variance	6.704141414
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
5	30	30.0%
9	22	22.0%
4	16	16.0%
2	13	13.0%
3	10	10.0%
1	9	9.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	9	9.0%
2	13	13.0%
3	10	10.0%
4	16	16.0%
5	30	30.0%
9	22	22.0%

Value	Count	Frequency (%)
9	22	22.0%
5	30	30.0%
4	16	16.0%
3	10	10.0%
2	13	13.0%
1	9	9.0%

_SMOKER3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

4.0	58
3.0	33
1.0	5
2.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4.0
2nd row	1.0
3rd row	4.0
4th row	4.0
5th row	4.0

Common Values

Value	Count	Frequency (%)
4.0	58	58.0%
3.0	33	33.0%
1.0	5	5.0%
2.0	4	4.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
4.0	58	58.0%
3.0	33	33.0%
1.0	5	5.0%
2.0	4	4.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
4	58	19.3%
3	33	11.0%
1	5	1.7%
2	4	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
4	58	29.0%
3	33	16.5%
1	5	2.5%
2	4	2.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
4	58	19.3%
3	33	11.0%
1	5	1.7%
2	4	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
4	58	19.3%
3	33	11.0%
1	5	1.7%
2	4	1.3%

_RFSMOK3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	91
2.0	9

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	91	91.0%
2.0	9	9.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	91	91.0%
2.0	9	9.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	91	30.3%
2	9	3.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	91	45.5%
2	9	4.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	91	30.3%
2	9	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	91	30.3%
2	9	3.0%

DRNKANY5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	66
1.0	34

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	66	66.0%
1.0	34	34.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	66	66.0%
1.0	34	34.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	66	22.0%
1	34	11.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	66	33.0%
1	34	17.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	66	22.0%
1	34	11.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	66	22.0%
1	34	11.3%

DROCDY3_
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	12
Distinct (%)	12.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.62

Minimum	5.4 × 10^-79
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	5.4 × 10^-79
5-th percentile	5.4 × 10^-79
Q1	5.4 × 10^-79
median	5.4 × 10^-79
Q3	3
95-th percentile	67
Maximum	100
Range	100
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	22.25734699
Coefficient of variation (CV)	2.582058815
Kurtosis	10.25180044
Mean	8.62
Median Absolute Deviation (MAD)	0
Skewness	3.271437138
Sum	862
Variance	495.3894949
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
5.4 × 10^-79	66	66.0%
3	11	11.0%
7	6	6.0%
100	4	4.0%
33	3	3.0%
14	3	3.0%
67	2	2.0%
29	1	1.0%
43	1	1.0%
17	1	1.0%
Other values (2)	2	2.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5.4 × 10^-79	66	66.0%
3	11	11.0%
7	6	6.0%
10	1	1.0%
13	1	1.0%
14	3	3.0%
17	1	1.0%
29	1	1.0%
33	3	3.0%
43	1	1.0%

Value	Count	Frequency (%)
100	4	4.0%
67	2	2.0%
43	1	1.0%
33	3	3.0%
29	1	1.0%
17	1	1.0%
14	3	3.0%
13	1	1.0%
10	1	1.0%
7	6	6.0%

_RFBING5
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	96
2.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	96	96.0%
2.0	4	4.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	96	96.0%
2.0	4	4.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	96	32.0%
2	4	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	96	48.0%
2	4	2.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	96	32.0%
2	4	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	96	32.0%
2	4	1.3%

_DRNKWEK
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	17.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3127.92

Minimum	5.4 × 10^-79
Maximum	99900
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.6 KiB

Quantile statistics

Minimum	5.4 × 10^-79
5-th percentile	5.4 × 10^-79
Q1	5.4 × 10^-79
median	5.4 × 10^-79
Q3	29
95-th percentile	991.35
Maximum	99900
Range	99900
Interquartile range (IQR)	29

Descriptive statistics

Standard deviation	17111.54323
Coefficient of variation (CV)	5.470582123
Kurtosis	29.84262253
Mean	3127.92
Median Absolute Deviation (MAD)	0
Skewness	5.587330995
Sum	312792
Variance	292804911.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
5.4 × 10^-79	66	66.0%
23	9	9.0%
93	4	4.0%
700	3	3.0%
99900	3	3.0%
140	2	2.0%
933	2	2.0%
100	2	2.0%
233	1	1.0%
117	1	1.0%
Other values (7)	7	7.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5.4 × 10^-79	66	66.0%
23	9	9.0%
47	1	1.0%
70	1	1.0%
93	4	4.0%
100	2	2.0%
117	1	1.0%
140	2	2.0%
233	1	1.0%
300	1	1.0%

Value	Count	Frequency (%)
99900	3	3.0%
4200	1	1.0%
2100	1	1.0%
933	2	2.0%
700	3	3.0%
600	1	1.0%
400	1	1.0%
300	1	1.0%
233	1	1.0%
140	2	2.0%

_RFDRHV6
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	94
9.0	3
2.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	94	94.0%
9.0	3	3.0%
2.0	3	3.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	94	94.0%
2.0	3	3.0%
9.0	3	3.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
2	3	1.0%
9	3	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	94	47.0%
2	3	1.5%
9	3	1.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
2	3	1.0%
9	3	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
2	3	1.0%
9	3	1.0%

_RFSEAT2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	95
2.0	5

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	95	95.0%
2.0	5	5.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	95	95.0%
2.0	5	5.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	95	31.7%
2	5	1.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	95	47.5%
2	5	2.5%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	95	31.7%
2	5	1.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	95	31.7%
2	5	1.7%

_RFSEAT3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

1.0	94
2.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	94	94.0%
2.0	6	6.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	94	94.0%
2.0	6	6.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
2	6	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
1	94	47.0%
2	6	3.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
2	6	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
1	94	31.3%
2	6	2.0%

_DRNKDRV
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

9.0	66
2.0	34

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	9.0
2nd row	2.0
3rd row	9.0
4th row	9.0
5th row	9.0

Common Values

Value	Count	Frequency (%)
9.0	66	66.0%
2.0	34	34.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
9.0	66	66.0%
2.0	34	34.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
9	66	22.0%
2	34	11.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
9	66	33.0%
2	34	17.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
9	66	22.0%
2	34	11.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
9	66	22.0%
2	34	11.3%

_AIDTST3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	1.6 KiB

2.0	81
1.0	17
9.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	300
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	2.0
3rd row	2.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	81	81.0%
1.0	17	17.0%
9.0	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	81	81.0%
1.0	17	17.0%
9.0	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	81	27.0%
1	17	5.7%
9	2	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	200	66.7%
Other Punctuation	100	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	50.0%
2	81	40.5%
1	17	8.5%
9	2	1.0%

Other Punctuation

Value	Count	Frequency (%)
.	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	300	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	81	27.0%
1	17	5.7%
9	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	300	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	100	33.3%
0	100	33.3%
2	81	27.0%
1	17	5.7%
9	2	0.7%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	_STATE	GENHLTH	PHYSHLTH	MENTHLTH	HLTHPLN1	PERSDOC2	MEDCOST	CHECKUP1	EXERANY2	SLEPTIM1	CVDINFR4	CVDCRHD4	CVDSTRK3	ASTHMA3	CHCSCNCR	CHCOCNCR	CHCCOPD1	HAVARTH3	ADDEPEV2	CHCKDNY1	DIABETE3	LASTDEN4	RMVTETH4	SEX1	MARITAL	EDUCA	RENTHOM1	VETERAN3	EMPLOY1	CHILDREN	INCOME2	DEAF	BLIND	DECIDE	DIFFWALK	DIFFDRES	DIFFALON	SMOKE100	USENOW3	ALCDAY5	FLUSHOT6	PNEUVAC4	SEATBELT	HIVTST6	HIVRISK5	QSTVER	QSTLANG	_METSTAT	_URBSTAT	_IMPRACE	_DUALUSE	_RFHLTH	_PHYS14D	_MENT14D	_HCVU651	_TOTINDA	_MICHD	_LTASTH1	_CASTHM1	_ASTHMS1	_DRDXAR1	_EXTETH3	_DENVST3	_PRACE1	_MRACE1	_HISPANC	_RACE	_RACEG21	_RACEGR3	_RACE_G1	_AGEG5YR	_AGE65YR	_AGE80	_AGE_G	_BMI5	_BMI5CAT	_RFBMI5	_CHLDCNT	_EDUCAG	_INCOMG	_SMOKER3	_RFSMOK3	DRNKANY5	DROCDY3_	_RFBING5	_DRNKWEK	_RFDRHV6	_RFSEAT2	_RFSEAT3	_DRNKDRV	_AIDTST3
object_id
0	1.0	2.0	30.0	88.0	1.0	1.0	2.0	1.0	2.0	7.0	2.0	2.0	2.0	2.0	1.0	2.0	2.0	1.0	2.0	2.0	3.0	1.0	1.0	2.0	3.0	6.0	1.0	2.0	2.0	88.0	6.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	2.0	2.0	1.0	1.0	1.0	3.0	1.0	9.0	2.0	2.0	1.0	1.0	3.0	1.0	2.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	13.0	2.0	80.0	6.0	2231.0	2.0	1.0	1.0	4.0	4.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
1	1.0	3.0	88.0	88.0	2.0	1.0	1.0	2.0	1.0	5.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	2.0	8.0	2.0	5.0	6.0	2.0	2.0	1.0	2.0	4.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	202.0	2.0	2.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	2.0	1.0	2.0	1.0	1.0	3.0	2.0	1.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	1.0	33.0	2.0	3328.0	4.0	2.0	3.0	4.0	2.0	1.0	2.0	1.0	7.000000e+00	1.0	9.300000e+01	1.0	1.0	1.0	2.0	2.0
2	1.0	5.0	10.0	88.0	1.0	1.0	2.0	1.0	1.0	7.0	2.0	2.0	1.0	2.0	2.0	2.0	2.0	2.0	1.0	2.0	1.0	1.0	7.0	2.0	3.0	4.0	1.0	2.0	7.0	88.0	3.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	2.0	1.0	1.0	9.0	2.0	2.0	1.0	9.0	1.0	2.0	1.0	1.0	3.0	2.0	9.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	12.0	2.0	76.0	6.0	2968.0	3.0	2.0	1.0	2.0	2.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
3	1.0	1.0	88.0	88.0	1.0	1.0	2.0	1.0	1.0	6.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	3.0	1.0	1.0	2.0	4.0	1.0	2.0	7.0	88.0	3.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	9.0	1.0	1.0	1.0	9.0	1.0	2.0	1.0	1.0	3.0	2.0	2.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	10.0	2.0	66.0	6.0	2726.0	3.0	2.0	1.0	2.0	2.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
4	1.0	2.0	88.0	88.0	1.0	2.0	2.0	1.0	2.0	6.0	2.0	1.0	2.0	1.0	2.0	2.0	2.0	2.0	2.0	2.0	4.0	1.0	7.0	2.0	3.0	5.0	1.0	2.0	7.0	88.0	99.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	9.0	2.0	1.0	2.0	2.0	1.0	2.0	9.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	13.0	2.0	80.0	6.0	3146.0	4.0	2.0	1.0	3.0	9.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
5	1.0	1.0	88.0	88.0	1.0	1.0	2.0	1.0	1.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	1.0	8.0	2.0	1.0	6.0	1.0	2.0	5.0	88.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	9.0	1.0	2.0	1.0	1.0	3.0	2.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	12.0	2.0	78.0	6.0	2496.0	2.0	1.0	1.0	4.0	5.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
6	1.0	2.0	88.0	88.0	1.0	1.0	2.0	1.0	1.0	7.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	1.0	8.0	2.0	1.0	6.0	1.0	2.0	5.0	2.0	99.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	201.0	2.0	2.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	3.0	2.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	6.0	1.0	47.0	4.0	2163.0	2.0	1.0	3.0	4.0	9.0	4.0	1.0	1.0	3.000000e+00	1.0	2.300000e+01	1.0	1.0	1.0	2.0	2.0
7	1.0	2.0	88.0	88.0	1.0	1.0	2.0	1.0	2.0	6.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	1.0	8.0	1.0	1.0	4.0	1.0	2.0	1.0	1.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	101.0	2.0	2.0	1.0	2.0	2.0	10.0	1.0	2.0	2.0	1.0	1.0	1.0	1.0	1.0	1.0	2.0	2.0	1.0	1.0	3.0	2.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	8.0	1.0	56.0	5.0	2705.0	3.0	2.0	2.0	2.0	5.0	3.0	1.0	1.0	1.400000e+01	1.0	1.000000e+02	1.0	1.0	1.0	2.0	2.0
8	1.0	3.0	5.0	88.0	1.0	1.0	2.0	1.0	1.0	7.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	3.0	1.0	8.0	2.0	2.0	6.0	2.0	2.0	1.0	88.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	888.0	1.0	2.0	1.0	1.0	2.0	10.0	1.0	1.0	1.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	2.0	1.0	1.0	3.0	2.0	1.0	1.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	6.0	1.0	48.0	4.0	2675.0	3.0	2.0	1.0	4.0	5.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	1.0
9	1.0	1.0	88.0	88.0	1.0	2.0	2.0	1.0	2.0	10.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	1.0	2.0	1.0	1.0	4.0	1.0	2.0	7.0	88.0	4.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	9.0	2.0	2.0	1.0	1.0	3.0	2.0	2.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	13.0	2.0	80.0	6.0	2699.0	3.0	2.0	1.0	2.0	2.0	3.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0

Last rows

	_STATE	GENHLTH	PHYSHLTH	MENTHLTH	HLTHPLN1	PERSDOC2	MEDCOST	CHECKUP1	EXERANY2	SLEPTIM1	CVDINFR4	CVDCRHD4	CVDSTRK3	ASTHMA3	CHCSCNCR	CHCOCNCR	CHCCOPD1	HAVARTH3	ADDEPEV2	CHCKDNY1	DIABETE3	LASTDEN4	RMVTETH4	SEX1	MARITAL	EDUCA	RENTHOM1	VETERAN3	EMPLOY1	CHILDREN	INCOME2	DEAF	BLIND	DECIDE	DIFFWALK	DIFFDRES	DIFFALON	SMOKE100	USENOW3	ALCDAY5	FLUSHOT6	PNEUVAC4	SEATBELT	HIVTST6	HIVRISK5	QSTVER	QSTLANG	_METSTAT	_URBSTAT	_IMPRACE	_DUALUSE	_RFHLTH	_PHYS14D	_MENT14D	_HCVU651	_TOTINDA	_MICHD	_LTASTH1	_CASTHM1	_ASTHMS1	_DRDXAR1	_EXTETH3	_DENVST3	_PRACE1	_MRACE1	_HISPANC	_RACE	_RACEG21	_RACEGR3	_RACE_G1	_AGEG5YR	_AGE65YR	_AGE80	_AGE_G	_BMI5	_BMI5CAT	_RFBMI5	_CHLDCNT	_EDUCAG	_INCOMG	_SMOKER3	_RFSMOK3	DRNKANY5	DROCDY3_	_RFBING5	_DRNKWEK	_RFDRHV6	_RFSEAT2	_RFSEAT3	_DRNKDRV	_AIDTST3
object_id
90	1.0	2.0	30.0	88.0	1.0	2.0	2.0	1.0	1.0	6.0	2.0	2.0	2.0	2.0	2.0	1.0	2.0	1.0	1.0	2.0	3.0	1.0	8.0	2.0	1.0	6.0	1.0	2.0	6.0	88.0	8.0	2.0	2.0	1.0	2.0	2.0	2.0	2.0	3.0	102.0	1.0	7.0	1.0	1.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	3.0	1.0	1.0	1.0	2.0	1.0	1.0	3.0	1.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	8.0	1.0	58.0	5.0	2524.0	3.0	2.0	1.0	4.0	5.0	4.0	1.0	1.0	2.900000e+01	1.0	4.000000e+02	1.0	1.0	1.0	2.0	1.0
91	1.0	4.0	14.0	88.0	1.0	1.0	2.0	1.0	2.0	4.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	2.0	1.0	3.0	1.0	7.0	2.0	1.0	5.0	1.0	2.0	7.0	88.0	5.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	2.0	2.0	1.0	1.0	2.0	3.0	1.0	9.0	2.0	2.0	1.0	1.0	3.0	1.0	9.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	11.0	2.0	73.0	6.0	3023.0	4.0	2.0	1.0	3.0	3.0	3.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
92	1.0	3.0	5.0	88.0	1.0	1.0	2.0	1.0	2.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	2.0	2.0	3.0	2.0	1.0	2.0	1.0	5.0	1.0	2.0	7.0	88.0	6.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	2.0	2.0	1.0	1.0	1.0	2.0	1.0	9.0	2.0	2.0	1.0	1.0	3.0	1.0	2.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	12.0	2.0	78.0	6.0	3320.0	4.0	2.0	1.0	3.0	4.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
93	1.0	5.0	3.0	2.0	1.0	1.0	2.0	1.0	2.0	6.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	3.0	3.0	2.0	4.0	2.0	2.0	2.0	8.0	88.0	77.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	3.0	888.0	2.0	2.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	2.0	1.0	2.0	2.0	2.0	9.0	2.0	2.0	1.0	1.0	3.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	12.0	2.0	78.0	6.0	2250.0	2.0	1.0	1.0	1.0	9.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
94	1.0	4.0	99.0	88.0	1.0	1.0	2.0	1.0	2.0	7.0	2.0	1.0	2.0	2.0	1.0	1.0	2.0	1.0	1.0	2.0	3.0	4.0	8.0	2.0	3.0	5.0	1.0	2.0	7.0	88.0	99.0	1.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	2.0	1.0	1.0	9.0	2.0	9.0	1.0	9.0	2.0	1.0	1.0	1.0	3.0	1.0	1.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	12.0	2.0	79.0	6.0	2539.0	3.0	2.0	1.0	3.0	9.0	3.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
95	1.0	2.0	88.0	88.0	1.0	1.0	2.0	2.0	1.0	6.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	2.0	8.0	1.0	1.0	6.0	1.0	2.0	1.0	2.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	202.0	2.0	2.0	1.0	1.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	3.0	2.0	1.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	6.0	1.0	49.0	4.0	2375.0	2.0	1.0	3.0	4.0	5.0	3.0	1.0	1.0	7.000000e+00	1.0	4.700000e+01	1.0	1.0	1.0	2.0	1.0
96	1.0	2.0	88.0	88.0	1.0	1.0	2.0	1.0	2.0	6.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	2.0	2.0	3.0	1.0	1.0	2.0	3.0	5.0	1.0	2.0	7.0	88.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	9.0	2.0	2.0	1.0	1.0	3.0	1.0	2.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	13.0	2.0	80.0	6.0	2141.0	2.0	1.0	1.0	3.0	1.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0
97	1.0	3.0	88.0	88.0	1.0	1.0	2.0	1.0	2.0	8.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	1.0	1.0	2.0	1.0	1.0	8.0	1.0	1.0	5.0	1.0	2.0	1.0	88.0	8.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	888.0	1.0	2.0	3.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	2.0	2.0	2.0	2.0	1.0	1.0	1.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	9.0	1.0	62.0	5.0	2650.0	3.0	2.0	1.0	3.0	5.0	4.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	2.0	2.0	9.0	2.0
98	1.0	2.0	20.0	88.0	1.0	1.0	2.0	1.0	2.0	10.0	1.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	3.0	8.0	3.0	1.0	1.0	5.0	1.0	2.0	1.0	88.0	7.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	230.0	2.0	2.0	5.0	2.0	2.0	10.0	1.0	2.0	2.0	1.0	1.0	1.0	3.0	1.0	9.0	2.0	1.0	1.0	1.0	3.0	2.0	2.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	13.0	2.0	80.0	6.0	3298.0	4.0	2.0	1.0	3.0	5.0	3.0	1.0	1.0	1.000000e+02	1.0	7.000000e+02	1.0	2.0	2.0	2.0	2.0
99	1.0	2.0	88.0	88.0	1.0	1.0	2.0	1.0	1.0	6.0	2.0	2.0	2.0	1.0	2.0	2.0	2.0	1.0	2.0	2.0	3.0	1.0	1.0	2.0	2.0	5.0	1.0	2.0	7.0	88.0	6.0	2.0	2.0	2.0	2.0	2.0	2.0	1.0	3.0	888.0	1.0	1.0	1.0	2.0	2.0	10.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	9.0	1.0	2.0	2.0	2.0	1.0	1.0	2.0	1.0	1.0	1.0	2.0	1.0	1.0	1.0	1.0	12.0	2.0	77.0	6.0	3399.0	4.0	2.0	1.0	3.0	4.0	3.0	1.0	2.0	5.400000e-79	1.0	5.400000e-79	1.0	1.0	1.0	9.0	2.0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation